At present, artificial intelligence has been well known and applied. In human-computer dialogues, a robot are usually produced to have the abilities to follow instructions, answer questions and guide services, and can specifically meet requirements of professional occasions such as family care, children care, healthcare, education, government offices, banks, hotels, tourist spots.
Currently, most information acquisition ways in people's lives are based on social scenarios. However, a majority of graph recognition products only serve as a separate tool and cannot be associated with original demand scenarios of users.
In single-round human-computer interactions, that is, a user performing inputs in a single operation or there being no correlation between multiple inputs of a user, an artificial intelligence can respond to queries of the user more accurately with the best output. But, if there is a certain correlation between the multiple inputs of the user, a multi-round input will be generated, so it requires an artificial intelligence to understand the inputs according to the context of the inputs. However, in the existing methods, identifying a multi-round property and a multi-round case is achieved mainly by using simple literal and syntactic features, but the multi-round property and a multi-round case cannot be accurately determined.
In addition, in a low context that the user input is relatively unclear, it is unable to accurately determine whether the user intends to make a multi-round search in the existing methods. In the existing methods, there is no modeling of a language model of search conditions in multiple inputs, so that in the low context, correct determination of a multi-round search purpose cannot be achieved.
Therefore, by the existing artificial intelligence, it is unable to output the best result meeting or satisfying the user's actual demand in a human-computer interaction of a multi-round case, a low-context case, or a low-context case of a multi-round interaction, such that the use initiative of the users is affected.